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The impact of antibiotic residue on sediment ecology at the watershed level is not yet fully understood. In this investigation, varying concentrations of oxytetracycline (OTC) and sulfadiazine (SD) were added to the overlying water of both the upper (0–10 cm) and bottom sediment
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The impact of antibiotic residue on sediment ecology at the watershed level is not yet fully understood. In this investigation, varying concentrations of oxytetracycline (OTC) and sulfadiazine (SD) were added to the overlying water of both the upper (0–10 cm) and bottom sediment (20–30 cm) layers at the watershed scale to evaluate the ecological impact on sediment habitats through the analysis of the activities of enzymes, namely urease (UA), alkaline phosphatase (APA), peroxidase (POA), and dehydrogenase (DHA). Results showed that the levels of UA and APA in the bottom sediment layers exceeded those in the top sediment layer upon reintroduction of antibiotics. Conversely, the fluctuations in DHA were notably reduced across various types of antibiotics and exposure concentrations in the bottom sediment layers. Within the top sediment layers, as the concentration of OTC exposure increased, there was a corresponding elevation in POA levels. However, the response of POA initially ascended and subsequently descended with rising SD exposure concentration, although it consistently exceeded the control levels. In contrast, the response of DHA displayed an inverse correlation with OTC exposure concentration but a direct correlation with SD exposure concentration. At the watershed scale, under antibiotic exposure, UA and DHA exhibited significantly higher levels upstream compared to downstream. Conversely, APA and POA appeared relatively stable across the watershed following the reintroduction of antibiotics. Moreover, DHA demonstrated a noticeable decreasing trend with increasing concentrations of OTC exposure. Environmental factors had a predominant influence, exceeding 40%, on enzyme activities during antibiotic reintroduction. Specifically, particle size significantly inhibited enzyme activity, while sediment nutrient conditions, including total carbon, nitrogen, and sulfur content, significantly enhanced enzyme activities. The study suggests that enzyme activities associated with antibiotic reintroduction in watershed sediments are established during stable stages in the bottom sediment layer or downstream sediment environment as part of sedimentary and transport processes. More research is required to explore the maintenance and evolution of antibiotic resistance profiles in the presence of long-term antibiotic residues.
Full article
The advancement of Augmented Reality (AR) technology has been remarkable, enabling the augmentation of user perception with timely information. This progress holds great promise in the field of interaction design. However, the mere advancement of technology is not enough to ensure widespread adoption.
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The advancement of Augmented Reality (AR) technology has been remarkable, enabling the augmentation of user perception with timely information. This progress holds great promise in the field of interaction design. However, the mere advancement of technology is not enough to ensure widespread adoption. The user dimension has been somewhat overlooked in AR research due to a lack of attention to user motivations, needs, usability, and perceived value. The critical aspects of AR technology tend to be overshadowed by the technology itself. To ensure appropriate future assessments, it is necessary to thoroughly examine and categorize all the methods used for AR technology validation. By identifying and classifying these evaluation methods, researchers and practitioners will be better equipped to develop and validate new AR techniques and applications. Therefore, comprehensive and systematic evaluations are critical to the advancement and sustainability of AR technology. This paper presents a theoretical framework derived from a cluster analysis of the most efficient evaluation methods for AR extracted from 399 papers. Evaluation methods were clustered according to the application domains and the human–computer interaction aspects to be investigated. This framework should facilitate rapid development cycles prioritizing user requirements, ultimately leading to groundbreaking interaction methods accessible to a broader audience beyond research and development centers.
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Heavy metal pollution in agricultural soils is one of the main problems in agricultural production worldwide, which threatens human health and the environment. To evaluate the pollution levels of heavy metals and the ecological risks in an agricultural area from Sánchez Ramírez Province,
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Heavy metal pollution in agricultural soils is one of the main problems in agricultural production worldwide, which threatens human health and the environment. To evaluate the pollution levels of heavy metals and the ecological risks in an agricultural area from Sánchez Ramírez Province, Dominican Republic, the concentration levels of heavy metals (Fe, Mn, Cr, Ni, Cu, Zn, Pb, and As) were measured using energy-dispersive X-ray fluorescence spectroscopy (EDXRF). Several pollution indices, including the geo-accumulation index (Igeo), enrichment factor (EF), and single pollution index (PI), were used to investigate the pollution status. The spatial distribution of different heavy metals in the studied soils was also determined. The mean concentrations of Fe, Mn, Cr, Ni, Cu, Zn, Pb, and As were 73735, 1616, 426; 34; 20; 200; 43; and 5 mg kg−1, respectively. These results indicated that the mean concentration of Cr, Cu, Zn, and Pb exceeded FAO-recommended levels for healthy agricultural soils. However, the potential ecological risks assessment indicated a low-risk status. The results obtained could help improve soil–rice–environment management practices and prevent heavy metal pollution in this type of production system, protecting the health of the local population and the environment.
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Manganese (Mn) is a heavy metal that can cause excessive Mn poisoning in plants, disrupting microstructural homeostasis and impairing growth and development. However, the specific response mechanisms of leaves to Mn poisoning have not been fully elucidated. This study revealed that Mn poisoning
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Manganese (Mn) is a heavy metal that can cause excessive Mn poisoning in plants, disrupting microstructural homeostasis and impairing growth and development. However, the specific response mechanisms of leaves to Mn poisoning have not been fully elucidated. This study revealed that Mn poisoning of soybean plants resulted in yellowing of old leaves. Physiological assessments of these old leaves revealed significant increases in the antioxidant enzymes activities (peroxidase (POD), superoxide dismutase (SOD), ascorbate peroxidase (APX), and catalase (CAT)) and elevated levels of malondialdehyde (MDA), proline, indoleacetic acid (IAA), and salicylic acid (SA), under 100 μM Mn toxicity. Conversely, the levels of abscisic acid (ABA), gibberellin 3 (GA3), and jasmonic acid (JA) significantly decreased. The Mn content in the affected leaves significantly increased, while the levels of Ca, Na, K, and Cu decreased. Transcriptome analysis revealed 2258 differentially expressed genes in the Mn-stressed leaves, 744 of which were upregulated and 1514 were downregulated; these genes included genes associated with ion transporters, hormone synthesis, and various enzymes. Quantitative RT-PCR (qRT-PCR) verification of fifteen genes confirmed altered gene expression in the Mn-stressed leaves. These findings suggest a complex gene regulatory mechanism under Mn toxicity and stress, providing a foundation for further exploration of Mn tolerance-related gene regulatory mechanisms in soybean leaves. Using the methods described above, this study will investigate the molecular mechanism of old soybean leaves’ response to Mn poisoning, identify key genes that play regulatory roles in Mn toxicity stress, and lay the groundwork for cultivating high-quality soybean varieties with Mn toxicity tolerance traits.
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Rabbit haemorrhagic disease viruses (RHDV) belong to the family Caliciviridae, genus Lagovirus europaeus, genogroup GI, comprising four genotypes GI.1–GI.4, of which the genotypes GI.1 and GI.2 are pathogenic RHD viruses, while the genotypes GI.3 and GI.4 are non-pathogenic RCV (Rabbit calicivirus [...] Read more.
Rabbit haemorrhagic disease viruses (RHDV) belong to the family Caliciviridae, genus Lagovirus europaeus, genogroup GI, comprising four genotypes GI.1–GI.4, of which the genotypes GI.1 and GI.2 are pathogenic RHD viruses, while the genotypes GI.3 and GI.4 are non-pathogenic RCV (Rabbit calicivirus) viruses. Among the pathogenic genotypes GI.1 and GI.2 of RHD viruses, an antigenic variant of RHDV, named RHDVa—now GI.1a–RHDVa, was distinguished in 1996; and in 2010, a variant of RHDV—named RHDVb, later RHDV2 and now GI.2–RHDV2/b—was described; and recombinants of these viruses were registered. Pathogenic viruses of the genotype GI.1 were the cause of a disease described in 1984 in China in domestic (Oryctolagus (O.) cuniculus domesticus) and wild (O. cuniculus) rabbits, characterised by a very rapid course and a mortality rate of 90–100%, which spread in countries all over the world and which has been defined since 1989 as rabbit haemorrhagic disease. It is now accepted that GI.1–RHDV, including GI.1a–RHDVa, cause the predetermined primary haemorrhagic disease in domestic and wild rabbits, while GI.2–RHDV2/b cause it not only in rabbits, including domestic rabbits’ young up to 4 weeks and rabbits immunised with rabbit haemorrhagic disease vaccine, but also in five various species of wild rabbits and seven different species of hares, as well as wild ruminants: mountain muskoxen and European badger. Among these viruses, haemagglutination-positive, doubtful and harmful viruses have been recorded and described and have been shown to form phylogenogroups, immunotypes, haematotypes and pathotypes, which, together with traits that alter and expand their infectious spectrum (rabbit, hare, wild ruminant, badger and various rabbit and hare species), are the determinants of their pathogenicity (infectivity) and immunogenicity and thus shape their virulence. These relationships are the aim of our consideration in this article.
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This study provides a comprehensive assessment of how the concept of energy is addressed in secondary and baccalaureate curricula in Spain, with a focus on alignment with the Sustainable Development Goals (SDGs) and the promotion of sustainable development. Through a qualitative analysis of
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This study provides a comprehensive assessment of how the concept of energy is addressed in secondary and baccalaureate curricula in Spain, with a focus on alignment with the Sustainable Development Goals (SDGs) and the promotion of sustainable development. Through a qualitative analysis of recent educational legislation, the research highlights the integration and contextualization of energy in different knowledge domains to promote understanding of current environmental challenges. Using a mixed methodology, the study examines curricular references to energy and categorizes them according to their emphasis on energy sources, consumption, technology, ethical awareness, and sustainability. The findings reveal a significant presence of the topic of energy, highlighting efforts to align educational curricula with the SDGs. Despite the significant focus on energy, the study identifies areas for improvement, including the need for greater interdisciplinary and practical integration that equips students to address energy challenges in innovative and sustainable ways.
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Network virtualization (NV) technology is the cornerstone of modern network architectures, offering significant advantages in resource utilization, flexibility, security, and streamlined management. By enabling the deployment of multiple virtual network requests (VNRs) within a single base network through virtual network embedding (VNE), NV
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Network virtualization (NV) technology is the cornerstone of modern network architectures, offering significant advantages in resource utilization, flexibility, security, and streamlined management. By enabling the deployment of multiple virtual network requests (VNRs) within a single base network through virtual network embedding (VNE), NV technology can substantially reduce the operational costs and energy consumption. However, the existing algorithms for energy-efficient VNE have limitations, including manual tuning for heuristic routing policies, inefficient feature extraction in traditional intelligent algorithms, and a lack of consideration of periodic traffic fluctuations. To address these limitations, this paper introduces a novel approach that leverages deep reinforcement learning (DRL) to enhance the efficiency of traditional methods. We employ graph convolutional networks (GCNs) for feature extraction, capturing the nuances of network graph structures, and integrate periodic traffic fluctuations as a key constraint in our model. This allows for the predictive embedding of VNRs that is both energy-efficient and responsive to dynamic network conditions. Our research aims to develop an energy-efficient VNE algorithm that dynamically adapts to network traffic patterns, thereby optimizing resource allocation and reducing energy consumption. Extensive simulation experiments demonstrate that our proposed algorithm achieves an average reduction of 22.4% in energy consumption and 41.0% in active substrate nodes, along with a 23.4% improvement in the acceptance rate compared to other algorithms.
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This work presents an electrochemical sensor detecting a fungicide-azoxystrobin (AZO) in aqueous environments. This AZO sensor utilizes a thin-film metal electrode (TFME) combined with an AZO-selective molecularly imprinted polymer (AZO–MIP). The AZO–MIP was directly generated on TFME through electrochemical polymerization from the solution
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This work presents an electrochemical sensor detecting a fungicide-azoxystrobin (AZO) in aqueous environments. This AZO sensor utilizes a thin-film metal electrode (TFME) combined with an AZO-selective molecularly imprinted polymer (AZO–MIP). The AZO–MIP was directly generated on TFME through electrochemical polymerization from the solution containing two functional monomers: aniline (Ani) and m-phenylenediamine (mPD), and the template: AZO, which was afterwards removed to form AZO-selective cavities in the polymer matrix. The AZO–MIP preparation was characterized by electrochemical and ellipsometry measurements. Optimization of the synthesis parameters, including the charge density applied during electrodeposition, the monomer-to-template ratio, was performed to enhance the sensor’s performance. The results demonstrated that the AZO sensor achieved a low limit of detection (LOD) of 3.6 nM and a limit of quantification (LOQ) of 11.8 nM in tap water, indicating its sensitivity in a complex aqueous environment. The sensor also exhibited satisfactory selectivity for AZO in both ultrapure and tap-water samples and achieved a good recovery (94–119%) for the target analyte. This study highlights the potential of MIP-based electrochemical sensors for the rapid and accurate detection of fungicide contaminants in water, contributing to the advancement of analytical tools for water-quality monitoring and risk assessment.
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Background: Continuous positive airway pressure (CPAP) is the first-line treatment for obstructive sleep apnoea (OSA). Maintaining adherence to CPAP in the long term is a clinical problem, and numerous factors have been identified that impact adherence. Although fully remote diagnostic and CPAP
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Background: Continuous positive airway pressure (CPAP) is the first-line treatment for obstructive sleep apnoea (OSA). Maintaining adherence to CPAP in the long term is a clinical problem, and numerous factors have been identified that impact adherence. Although fully remote diagnostic and CPAP services were frequently utilised during the COVID-19 pandemic for patients with OSA, long-term adherence data have not been published. The aim of this service evaluation project was to describe the long-term adherence to CPAP. We also analysed factors that are associated with it. Methods: two-hundred and eighty patients diagnosed with OSA and set up on CPAP remotely during the first wave of the COVID-19 pandemic as part of routine clinical practice were analysed. Results: One-hundred and seven patients (38%) were fully adherent to CPAP at 24 months, determined by at least 4 h of usage on at least 70% of the days. Of the factors analysed, body mass index, disease severity, driving status and the presence of depression were related to long-term adherence (all p < 0.05). Conclusions: with the likelihood of future pandemics similar to COVID-19, our data provide evidence that fully remote pathways for management of patients with OSA can be designed and be sustainable with good long-term adherence.
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Intelligent devices, when subjected to multiple interactions, tend to generate electromagnetic pollution, which can disrupt the normal functioning of electronic components. Ferrite, which acts as a microwave-absorbing material (MAM), offers a promising strategy to overcome this issue. To further enhance the
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Intelligent devices, when subjected to multiple interactions, tend to generate electromagnetic pollution, which can disrupt the normal functioning of electronic components. Ferrite, which acts as a microwave-absorbing material (MAM), offers a promising strategy to overcome this issue. To further enhance the microwave absorption properties of ferrite MAM, numerous works have been conducted, including ion doping and combining with other materials. Notably, the microstructure is also key factor that affects the microwave absorption properties of ferrite-based MAM. Thus, this article provides a comprehensive overview of research progress on the influence of the microstructure on ferrite-based MAM. MAMs with sheet and layered structures are also current important research directions. For core-shell structure composites, the solid core-shell structure, hollow core-shell structure, yolk-eggshell structure, and non-spherical core-shell structure are introduced. For porous composites, the biomass porous structure and other porous structures are presented. Finally, the development trends are summarized, and prospects for the structure design and preparation of high-performance MAMs are predicted.
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This paper studies the stability of a real-world wind farm, Bison Wind Generation System (BWGS) in the state of North Dakota in the United States. BWGS uses an AC collector grid rated at 34.5 kV and a symmetrical bipolar high-voltage DC (HVDC) transmission
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This paper studies the stability of a real-world wind farm, Bison Wind Generation System (BWGS) in the state of North Dakota in the United States. BWGS uses an AC collector grid rated at 34.5 kV and a symmetrical bipolar high-voltage DC (HVDC) transmission grid rated at ±250 kV. The HVDC line transfers a total power of 0.5 GW, while both the HVDC rectifier and inverter substations use line-commuted converters (LCCs). The LCC-based rectifier adopts constant DC current control to regulate HVDC current, while the inverter operates in constant extinction angle control mode to maintain a fixed HVDC voltage. This paper proposes a frequency scan-based approach to obtain the d–q impedance model of (i) BWGS AC collector grids with Type 4 wind turbines that use permanent magnet synchronous generators (PMSGs) and two fully rated converters, and (ii) an LCC-HVDC system. The impedance frequency response of the BWGS is acquired by exciting the AC collector grid and LCC-HVDC with multi-sine voltage perturbations during its steady-state operation. The resulting voltage and current signals are subjected to a fast Fourier transform (FFT) to extract frequency components. By analyzing the impedance frequency response measurement of BWGS, a linear time–invariant (LTI) representation of its dynamics is obtained using the vector fitting (VF) technique. Finally, a Bode plot is applied, considering the impedance of the BWGS and grid to perform stability analyses. This study examines the influence of the short circuit ratio (SCR) of the grid and the phase lock loop (PLL) frequency bandwidth on the stability of the overall system. The findings provide valuable insights for the design and verification of an AC collector and LCC-based HVDC transmission systems. The findings suggest that the extraction of the impedance model of a real-world wind farm, achieved through frequency scanning and subsequent representation as an LTI system using VF, is regarded as a robust, suitable, and accurate methodology for investigating the dynamics, unstable operating conditions, and control interaction of the wind farm and LCC-HVDC system with the AC grid.
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Background: Bone-anchored maxillary protraction (BAMP) aims to correct midfacial deficiencies, with proven positive skeletal changes without potential unwanted side effects. However, the influence of BAMP treatment on facial soft tissues, particularly in subjects with complete unilateral cleft lip, alveolus, and palate (CUCLAP), remains
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Background: Bone-anchored maxillary protraction (BAMP) aims to correct midfacial deficiencies, with proven positive skeletal changes without potential unwanted side effects. However, the influence of BAMP treatment on facial soft tissues, particularly in subjects with complete unilateral cleft lip, alveolus, and palate (CUCLAP), remains unclear. Methods: This single-center longitudinal cohort study examined the effects of 1.5 years of BAMP treatment on facial soft tissues in growing subjects with complete unilateral cleft lip, alveolus, and palate. The sample consisted of 25 patients, age range 9.7 to 12.6 years. Three-dimensional surface models derived from CBCT scans were superimposed on stable structures of the anterior cranial base and on the occipital area posterior of the foramen magnum to assess three-dimensional changes due to growth and BAMP therapy. Results: The results revealed a moderate positive correlation (Pearson’s correlation coefficient from 0.203 to 0.560) between changes in hard tissue and soft tissue; some correlations were found to be weak (<0.300). Linear changes in soft tissue following BAMP were in the same direction as skeletal changes, showing downward, forward, and outward displacement. The only exception was in the vertical dimension. The lower facial third showed a slight but significant reduction, mainly in lip length (−1.2 mm), whereas the middle facial third showed a small increase (1.1 mm). Conclusions: It was concluded that during BAMP, soft tissue changes occur in the same direction as skeletal changes, although with a larger variability and less pronounced effects.
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Cement production requires considerable energy and natural resources, severely impacting the environment due to harmful gas emissions. Coal bottom ash (CBA) and coal boiler slag (CBS), byproducts of coal-fired powerplants having pozzolanic properties, can be mechanically ground and replace cement in concrete, which
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Cement production requires considerable energy and natural resources, severely impacting the environment due to harmful gas emissions. Coal bottom ash (CBA) and coal boiler slag (CBS), byproducts of coal-fired powerplants having pozzolanic properties, can be mechanically ground and replace cement in concrete, which reduces waste in landfills, preserves natural resources, and reduces health hazards. This study was performed to determine the optimum cement replacement amount of ground CBA (GCBA) and ground CBS (GCBS) in concrete, which was 10% for GCBA and 5% for GCBS. GCBA-based concrete exhibited superior tensile strength, modulus of elasticity, and durability compared to the control. In the Rapid Chloride Penetration Test, 10% GCBA concrete resulted in 2026 coulombs at 56 days, compared to 3405 coulombs for the control, indicating more resistance to chloride penetration. Incorporating 2.5% nanoclay in GCBA-based concrete increased the optimum GCBA content by 5%, and the compressive strength of 15% GCBA concrete increased by 4 MPa. The mortar consisting of the finest GCBA(L1) having Blaine fineness of 3072 g/cm2 yielded the highest compressive strength (32.7 MPa). The study discovered that the compressive strength of GCBA and GCBS-based mortars increases with fineness, and meeting the recommended fineness limit in ASTM C618 enhances concrete or mortar properties.
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Leguminous green manure (LGM) has a reputation for improving crop productivity. However, little is known about the beneficial interactions with straw on crop yield and nutrient (N, P, K) use efficiency. Herein, a 9-year field experiment (from 2015 to 2023) containing three treatments—(1)
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Leguminous green manure (LGM) has a reputation for improving crop productivity. However, little is known about the beneficial interactions with straw on crop yield and nutrient (N, P, K) use efficiency. Herein, a 9-year field experiment (from 2015 to 2023) containing three treatments—(1) chemical fertilizer as the control (CK), (2) NPK + straw return (Straw) and (3) NPK + straw return with LGM (Straw + LGM)—was conducted to investigate whether the combined application of LGM and straw can increase productivity and nutrient use efficiency in the wheat–maize–sunflower diversified cropping rotation. The results showed that in the third rotation (2021–2023), Straw + LGM significantly increased wheat yield by 10.2% and maize yield by 19.9% compared to CK. The total equivalent yield under Straw + LGM was the highest (26.09 Mg ha−1), exceeding Straw and CK treatments by 2.7% and 12.3%, respectively. For each 2 Mg ha−1 increase in straw returned to the field, sunflower yield increased by 0.2 Mg ha−1, whereas for each 1 Mg ha−1 increase in LGM yield from the previous crop, sunflower yield increased by 0.45 Mg ha−1. Compared to CK, the co-application of LGM and straw increased the N use efficiency of maize in the first and third rotation cycle by 70.6% and 55.8%, respectively, and the P use efficiency by 147.8% in the third rotation cycle. Moreover, Straw treatment led to an increase of net income from wheat and sunflower by 14.5% and 44.6%, while Straw + LGM increased the net income from maize by 15.8% in the third rotation cycle. Combining leguminous green manure with a diversified cropping rotation has greater potential to improve nutrient use efficiency, crop productivity and net income, which can be recommended as a sustainable agronomic practice in the Hetao District, Northwest China.
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Lumbar fusion surgery for treating degenerative spinal diseases has undergone significant advancements in recent years. In addition to posterior instrumentation, anterior interbody fusion techniques have been developed along with various cages for interbody fusion. Recently, expandable cages capable of altering height, lordotic angle,
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Lumbar fusion surgery for treating degenerative spinal diseases has undergone significant advancements in recent years. In addition to posterior instrumentation, anterior interbody fusion techniques have been developed along with various cages for interbody fusion. Recently, expandable cages capable of altering height, lordotic angle, and footprint within the disc space have garnered significant attention. In this manuscript, we review the current status, clinical outcomes, and future prospects of expandable cages for lumbar interbody fusion based on the existing literature. Expandable cages are suitable for minimally invasive spinal surgeries. Small-sized cages can be inserted and subsequently expanded to a larger size within the disc space. While expandable cages generally demonstrate superior clinical outcomes compared to static cages, some studies have suggested comparable or even poorer outcomes with expandable cages than static cages. Careful interpretation through additional long-term follow-ups is required to assess the utility of expandable cages. If these shortcomings are addressed and the advantages are further developed, expandable cages could become suitable surgical instruments for minimally invasive spinal surgeries.
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Thin copper plate is widely used in architecture, transportation, heavy equipment, and integrated circuit substrates due to its unique properties. However, it is challenging to identify surface defects in copper strips arising from various manufacturing stages without direct contact. A laser ultrasonic inspection
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Thin copper plate is widely used in architecture, transportation, heavy equipment, and integrated circuit substrates due to its unique properties. However, it is challenging to identify surface defects in copper strips arising from various manufacturing stages without direct contact. A laser ultrasonic inspection system was developed based on the Lamb wave (LW) produced by a laser pulse. An all-fiber laser heterodyne interferometer is applied for measuring the ultrasonic signal in combination with an automatic scanning system, which makes the system flexible and compact. A 3-D model simulation of an H62 brass specimen was carried out to determine the LW spatial-temporal wavefield by using the COMSOL Multiphysics software. The characteristics of the ultrasonic wavefield were extracted through continuous wavelet transform analysis. This demonstrates that the A0 mode could be used in defect detection due to its slow speed and vibrational direction. Furthermore, an ultrasonic wave at the center frequency of 370 kHz with maximum energy is suitable for defect detection. In the experiment, the size and location of the defect are determined by the time difference of the transmitted wave and reflected wave, respectively. The relative error of the defect position is 0.14% by averaging six different receiving spots. The width of the defect is linear to the time difference of the transmitted wave. The goodness of fit can reach 0.989, and it is in good agreement with the simulated one. The experimental error is less than 0.395 mm for a 5 mm width of defect. Therefore, this validates that the technique can be potentially utilized in the remote defect detection of thin copper plates.
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The use of renewable energy sources, such as wind power, has received more attention in China, and wind turbine system reliability has become more important. Based on existing research, this study proposes a state reliability prediction model for wind turbine systems based on
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The use of renewable energy sources, such as wind power, has received more attention in China, and wind turbine system reliability has become more important. Based on existing research, this study proposes a state reliability prediction model for wind turbine systems based on XGBoost–LSTM. By considering the dynamic variability of the weight fused by the algorithm, under the irregular fluctuation of the same parameter with time in nonlinear systems, it reduces the algorithm defects in the prediction process. The improved algorithm is validated by arithmetic examples, and the results show that the root mean square error value (hereinafter abbreviated as RMSE) and the mean absolute error value (hereinafter abbreviated as MAPE) of the improved XGBoost–LSTM algorithm are decreased compared with those for the LSTM and XGBoost algorithms, among which the RMSE is reduced by 8.26% and 4.15% and the MAPE is reduced by 24.56% and 27.99%, respectively; its goodness-of-fit R2 value is closer to 1. This indicates that the algorithm proposed in this paper reduces the existing defects present in some current algorithms, and the prediction accuracy is effectively improved, which is of great value in improving the reliability of the system.
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The sweetness is an important parameter for the quality of Cuixiang kiwifruit. The quick and accurate assessment of sweetness is necessary for farmers to make timely orchard management and for consumers to make purchasing choices. The objective of the study was to propose
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The sweetness is an important parameter for the quality of Cuixiang kiwifruit. The quick and accurate assessment of sweetness is necessary for farmers to make timely orchard management and for consumers to make purchasing choices. The objective of the study was to propose an effective physical method for determining the sweetness of fresh kiwifruit based on fruit hyperspectral reflectance in 400–2500 nm. In this study, the visible and near-infrared spectral (Vis/NIR) reflectance and sweetness values of kiwifruit were measured at different time periods after the fruit matured in 2021 and 2022. The multiplicative scatter correction (MSC) and standard normal variable (SNV) transformation were used for spectral denoising. The successive projections algorithm (SPA) and competitive adaptive reweighted sampling (CARS) methods were employed to select the most effective features for sweetness, and then the features were used as the inputs of partial least squares (PLS), least squares support vector machine (LSSVM), back propagation neural network (BP), and multiple linear regression (MLR) models to explore the best way of sweetness predicting. The study indicated that the most sensitive features were in the blue and red regions and the 970, 1200, and 1400 nm. The sweetness estimation model constructed by using the data of the whole harvest period from August to October performed better than the models constructed by each harvest period. Overall results indicated that hyperspectral reflectance incorporated with MSC-SPA-LSSVM could explain up to 79% of the variability in kiwifruit sweetness, which could be applied as an alternative fast and accurate method for the non-destructive determination of the sweetness of kiwifruit. This research could partially provide a theoretical basis for the development of nondestructive instrumentation for the detection of kiwifruit sweetness.
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In the present study, a novel end-to-end automatic speech recognition (ASR) framework, namely, ResNeXt-Mssm-CTC, has been developed for air traffic control (ATC) systems. This framework is built upon the Multi-Head State-Space Model (Mssm) and incorporates transfer learning techniques. Residual Networks with Cardinality (ResNeXt)
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In the present study, a novel end-to-end automatic speech recognition (ASR) framework, namely, ResNeXt-Mssm-CTC, has been developed for air traffic control (ATC) systems. This framework is built upon the Multi-Head State-Space Model (Mssm) and incorporates transfer learning techniques. Residual Networks with Cardinality (ResNeXt) employ multi-layered convolutions with residual connections to augment the extraction of intricate feature representations from speech signals. The Mssm is endowed with specialized gating mechanisms, which incorporate parallel heads that acquire knowledge of both local and global temporal dynamics in sequence data. Connectionist temporal classification (CTC) is utilized in the context of sequence labeling, eliminating the requirement for forced alignment and accommodating labels of varying lengths. Moreover, the utilization of transfer learning has been shown to improve performance on the target task by leveraging knowledge acquired from a source task. The experimental results indicate that the model proposed in this study exhibits superior performance compared to other baseline models. Specifically, when pretrained on the Aishell corpus, the model achieves a minimum character error rate (CER) of 7.2% and 8.3%. Furthermore, when applied to the ATC corpus, the CER is reduced to 5.5% and 6.7%.
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This article explores the mechanism for constructing and the path for implementing an industrial brain in the development of smart cities, with a focus on the case of the Yiwu knitting industry platform in China. Accordingly, our study involved a literature review, questionnaire
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This article explores the mechanism for constructing and the path for implementing an industrial brain in the development of smart cities, with a focus on the case of the Yiwu knitting industry platform in China. Accordingly, our study involved a literature review, questionnaire survey, data analysis, qualitative comparative analysis (QCA), and discussion. Our key finding was that the manufacturing brain evolves in three distinct stages: platform creation, growth, and expansion. The mechanisms of implementing these are functional development, trust creation, and value co-creation, respectively. Specifically, functional development marks the commencement of the industrial brain’s construction, which involves enterprise demand analysis, capability bottleneck identification, data value formation, and platform architecture simplification. Trust building serves as the central mechanism of evolving the manufacturing brain, comprising institutional, relational, and computational trust. Lastly, value co-creation proceeds, which is pivotal for a business paradigm revolution, encompassing connection, linkage, and integration. The main theoretical contribution of this article is to propose a normative analytical framework for revealing the mechanism of construction and the path of implementation of industrial platforms in smart city development. Meanwhile, in its practical contribution, this article provides policy guidance, as developed through our analysis of how an industrial platform can promote the transformation and upgrading of the urban manufacturing industry, to realize smart city construction and the economy and society’s coordinated development.
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This work is focused on the characterization of the composition of a CO2 supercritical fluid extract of Aquilaria sinensis (Chinese agarwood) collected in the Dongguan area (China) and infected by mechanical methods. The constituents of this extract were analyzed by gas chromatography–mass
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This work is focused on the characterization of the composition of a CO2 supercritical fluid extract of Aquilaria sinensis (Chinese agarwood) collected in the Dongguan area (China) and infected by mechanical methods. The constituents of this extract were analyzed by gas chromatography–mass spectrometry (GC-MS) and quantified accurately by gas chromatography with a flame ionization detector (GC-FID), using an internal reference and predicted response factors. Since a significant number of components of this extract remained non-identified after the initial GC-MS analysis of the whole extract, its fractionation by chromatography on silica gel helped to characterize several additional constituents by isolation and structural analysis by NMR spectroscopy. The main components are the classical agarwood chromones (Flindersia chromone and its mono-, di-, and trimethoxylated analogues (respectively, 11.01% and 0.11–4.02%) along with sesquiterpenic constituents typically found in agarwood essential oils, like baimuxinal (1.90%) and kusunol (1.24%), as well as less common selinane dialdehydes (1.58–2.27%) recently described in the literature. Moreover, the structure and stereochemistry of a new sesquiterpenic alcohol, 14β,15β-dimethyl-7αH-eremophila-9,11-dien-8β-ol (0.67%), was determined unambiguously by the combination of structural analysis (NMR, MS), hemisynthesis, and total synthesis, leading to dihydrokaranone and a neopetasane epimer.
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Achieving the goal of integrated urban–rural development is to achieve a spatially balanced development of the constituent elements of urban–rural relations in China. Rural populations and land dedicated to construction are the main components of the countryside in traditional agricultural areas; they play
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Achieving the goal of integrated urban–rural development is to achieve a spatially balanced development of the constituent elements of urban–rural relations in China. Rural populations and land dedicated to construction are the main components of the countryside in traditional agricultural areas; they play an important role in the development of the countryside itself in terms of urban and rural land use and in the formation of urban and rural development patterns. This study analyzes the spatial and temporal changes in rural populations and construction land at the township level, alongside assessing various forms and the extent of coupled development. Herein, we consider the role of urban–rural attractiveness and propose a framework for relationships between urban and rural development based on different forms of coupled development; a model of urban–rural forces is constructed to determine spatial patterns of urban–rural development at the township level that may transpire in the future. Our study shows that the rural population and construction land in the study area are characterized by significant spatial and temporal dynamics, indicating that traditional rural areas are in a process of rapid development and change. The results of our measurements of township-level coupling indicate that there exist four development patterns within urban–rural development: the A-type is most likely to produce new cities or satellite towns in the future and form new urban areas; the B-type is the area most likely to cease and be annexed to other villages or cities to meet building targets; the C-type comprises areas to be focused on in the future to attract populations and strictly control the growth of rural construction land areas (to avoid land transforming into the B-type); and the D-type refers to lands upon which regional township centers may develop in the future, becoming an area devoted to rural revitalization. The A-type and D-type are prioritized for the allocation of construction land, which can be contracted from types B and C. The results of this study have provided important reference for the formulation of population and construction land control policies in accordance with local conditions and the realization of integrated urban and rural development strategies.
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In recent years, biofuels have gained considerable prominence in response to growing concerns about resource scarcity and environmental pollution. Previous investigations have revealed that the appropriate blending of iso-propanol–butanol–ethanol (IBE) into diesel significantly improves both the c combustion efficiency and emission performance of
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In recent years, biofuels have gained considerable prominence in response to growing concerns about resource scarcity and environmental pollution. Previous investigations have revealed that the appropriate blending of iso-propanol–butanol–ethanol (IBE) into diesel significantly improves both the c combustion efficiency and emission performance of internal combustion engines (ICEs). However, the combustion mechanism of IBE–diesel for the numerical studies of engines has not reached maturity. In this study, a skeletal IBE–diesel multi-component mechanism, comprising 157 species and 603 reactions, was constructed using the decoupling method. It was formulated by amalgamating the reduced fuel-related sub-mechanisms derived from diesel surrogates (n-dodecane, iso-cetane, iso-octane, toluene, and decalin) and n-butanol, along with the detailed core sub-mechanisms of C1, C2, C3, CO, and H2. The constructed mechanism is capable of better matching the physical and chemical properties of actual diesel fuel. Extensive validation, including ignition delay, laminar flame speed, a premixed flame species profile, and engine experimental data, confirms the reliability of the mechanism in engine numerical studies. Subsequent investigations reveal that as the IBE blend ratio and EGR rate increase, the ignition delay exhibits an increase, while the combustion duration experiences a decrease. Blending IBE into diesel, along with a specific EGR rate, proves effective in simultaneously reducing NOx and soot emissions.
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